AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics.

Cellular composition and anatomical organization influence normal and aberrant organ functions. Emerging spatial single-cell proteomic assays such as Image Mass Cytometry (IMC) and Co-Detection by Indexing (CODEX) have facilitated the study of cellular composition and organization by enabling high-throughput measurement of cells and their localization directly in intact tissues. However, annotation of cell types and quantification of their relative localization in tissues remain challenging. To address these unmet needs for atlas-scale datasets like Human Pancreas Analysis Program (HPAP), we develop AnnoSpat (Annotator and Spatial Pattern Finder) that uses neural network and point process algorithms to automatically identify cell types and quantify cell-cell proximity relationships. Our study of data from IMC and CODEX shows the higher performance of AnnoSpat in rapid and accurate annotation of cell types compared to alternative approaches. Moreover, the application of AnnoSpat to type 1 diabetic, non-diabetic autoantibody-positive, and non-diabetic organ donor cohorts recapitulates known islet pathobiology and shows differential dynamics of pancreatic polypeptide (PP) cell abundance and CD8+ T cells infiltration in islets during type 1 diabetes progression.

Intrinsically disordered domain of transcription factor TCF-1 is required for T cell developmental fidelity.

In development, pioneer transcription factors access silent chromatin to reveal lineage-specific gene programs. The structured DNA-binding domains of pioneer factors have been well characterized, but whether and how intrinsically disordered regions affect chromatin and control cell fate is unclear. Here, we report that deletion of an intrinsically disordered region of the pioneer factor TCF-1 (termed L1) leads to an early developmental block in T cells. The few T cells that develop from progenitors expressing TCF-1 lacking L1 exhibit lineage infidelity distinct from the lineage diversion of TCF-1-deficient cells. Mechanistically, L1 is required for activation of T cell genes and repression of GATA2-driven genes, normally reserved to the mast cell and dendritic cell lineages. Underlying this lineage diversion, L1 mediates binding of TCF-1 to its earliest target genes, which are subject to repression as T cells develop. These data suggest that the intrinsically disordered N terminus of TCF-1 maintains T cell lineage fidelity.

EBF1 nuclear repositioning instructs chromatin refolding to promote therapy resistance in T leukemic cells.

Chromatin misfolding has been implicated in cancer pathogenesis; yet, its role in therapy resistance remains unclear. Here, we systematically integrated sequencing and imaging data to examine the spatial and linear chromatin structures in targeted therapy-sensitive and -resistant human T cell acute lymphoblastic leukemia (T-ALL). We found widespread alterations in successive layers of chromatin organization including spatial compartments, contact domain boundaries, and enhancer positioning upon the emergence of targeted therapy resistance. The reorganization of genome folding structures closely coincides with the restructuring of chromatin activity and redistribution of architectural proteins. Mechanistically, the derepression and repositioning of the B-lineage-determining transcription factor EBF1 from the heterochromatic nuclear envelope to the euchromatic interior instructs widespread genome refolding and promotes therapy resistance in leukemic T cells. Together, our findings suggest that lineage-determining transcription factors can instruct changes in genome topology as a driving force for epigenetic adaptations in targeted therapy resistance.

TooManyPeaks identifies drug-resistant-specific regulatory elements from single-cell leukemic epigenomes.

Emerging single-cell epigenomic assays are used to investigate the heterogeneity of chromatin activity and its function. However, identifying cells with distinct regulatory elements and clearly visualizing their relationships remains challenging. To this end, we introduce TooManyPeaks to address the need for the simultaneous study of chromatin state heterogeneity in both rare and abundant subpopulations. Our analyses of existing data from three widely used single-cell assays for transposase-accessible chromatin using sequencing (scATAC-seq) show the superior performance of TooManyPeaks in delineating and visualizing pure clusters of rare and abundant subpopulations. Furthermore, the application of TooManyPeaks to new scATAC-seq data from drug-naive and drug-resistant leukemic T cells clearly visualizes relationships among these cells and stratifies a rare "resistant-like" drug-naive sub-clone with distinct cis-regulatory elements.

ZMYND8-regulated IRF8 transcription axis is an acute myeloid leukemia dependency.

The transformed state in acute leukemia requires gene regulatory programs involving transcription factors and chromatin modulators. Here, we uncover an IRF8-MEF2D transcriptional circuit as an acute myeloid leukemia (AML)-biased dependency. We discover and characterize the mechanism by which the chromatin "reader" ZMYND8 directly activates IRF8 in parallel with the MYC proto-oncogene through their lineage-specific enhancers. ZMYND8 is essential for AML proliferation in vitro and in vivo and associates with MYC and IRF8 enhancer elements that we define in cell lines and in patient samples. ZMYND8 occupancy at IRF8 and MYC enhancers requires BRD4, a transcription coactivator also necessary for AML proliferation. We show that ZMYND8 binds to the ET domain of BRD4 via its chromatin reader cassette, which in turn is required for proper chromatin occupancy and maintenance of leukemic growth in vivo. Our results rationalize ZMYND8 as a potential therapeutic target for modulating essential transcriptional programs in AML.

ALC1 links chromatin accessibility to PARP inhibitor response in homologous recombination-deficient cells.

The response to poly(ADP-ribose) polymerase inhibitors (PARPi) is dictated by homologous recombination (HR) DNA repair and the abundance of lesions that trap PARP enzymes. It remains unclear, however, if the established role of PARP in promoting chromatin accessibility impacts viability in these settings. Using a CRISPR-based screen, we identified the PAR-binding chromatin remodeller ALC1/CHD1L as a key determinant of PARPi toxicity in HR-deficient cells. ALC1 loss reduced viability of breast cancer gene (BRCA)-mutant cells and enhanced sensitivity to PARPi by up to 250-fold, while overcoming several resistance mechanisms. ALC1 deficiency reduced chromatin accessibility concomitant with a decrease in the association of base damage repair factors. This resulted in an accumulation of replication-associated DNA damage, increased PARP trapping and a reliance on HR. These findings establish PAR-dependent chromatin remodelling as a mechanistically distinct aspect of PARPi responses and therapeutic target in HR-deficient cancers.

TooManyCells identifies and visualizes relationships of single-cell clades.

Identifying and visualizing transcriptionally similar cells is instrumental for accurate exploration of the cellular diversity revealed by single-cell transcriptomics. However, widely used clustering and visualization algorithms produce a fixed number of cell clusters. A fixed clustering 'resolution' hampers our ability to identify and visualize echelons of cell states. We developed TooManyCells, a suite of graph-based algorithms for efficient and unbiased identification and visualization of cell clades. TooManyCells introduces a visualization model built on a concept intentionally orthogonal to dimensionality-reduction methods. TooManyCells is also equipped with an efficient matrix-free divisive hierarchical spectral clustering different from prevalent single-resolution clustering methods. TooManyCells enables multiresolution and multifaceted exploration of single-cell clades. An advantage of this paradigm is the immediate detection of rare and common populations that outperforms popular clustering and visualization algorithms, as demonstrated using existing single-cell transcriptomic data sets and new data modeling drug-resistance acquisition in leukemic T cells.

Genetic Variation in Type 1 Diabetes Reconfigures the 3D Chromatin Organization of T Cells and Alters Gene Expression.

Genetics is a major determinant of susceptibility to autoimmune disorders. Here, we examined whether genome organization provides resilience or susceptibility to sequence variations, and how this would contribute to the molecular etiology of an autoimmune disease. We generated high-resolution maps of linear and 3D genome organization in thymocytes of NOD mice, a model of type 1 diabetes (T1D), and the diabetes-resistant C57BL/6 mice. Multi-enhancer interactions formed at genomic regions harboring genes with prominent roles in T cell development in both strains. However, diabetes risk-conferring loci coalesced enhancers and promoters in NOD, but not C57BL/6 thymocytes. 3D genome mapping of NODxC57BL/6 F1 thymocytes revealed that genomic misfolding in NOD mice is mediated in cis. Moreover, immune cells infiltrating the pancreas of humans with T1D exhibited increased expression of genes located on misfolded loci in mice. Thus, genetic variation leads to altered 3D chromatin architecture and associated changes in gene expression that may underlie autoimmune pathology.

Oncogenic Notch Promotes Long-Range Regulatory Interactions within Hyperconnected 3D Cliques.

Chromatin loops enable transcription-factor-bound distal enhancers to interact with their target promoters to regulate transcriptional programs. Although developmental transcription factors such as active forms of Notch can directly stimulate transcription by activating enhancers, the effect of their oncogenic subversion on the 3D organization of cancer genomes is largely undetermined. By mapping chromatin looping genome-wide in Notch-dependent triple-negative breast cancer and B cell lymphoma, we show that beyond the well-characterized role of Notch as an activator of distal enhancers, Notch regulates its direct target genes by instructing enhancer repositioning. Moreover, a large fraction of Notch-instructed regulatory loops form highly interacting enhancer and promoter spatial clusters termed "3D cliques." Loss- and gain-of-function experiments show that Notch preferentially targets hyperconnected 3D cliques that regulate the expression of crucial proto-oncogenes. Our observations suggest that oncogenic hijacking of developmental transcription factors can dysregulate transcription through widespread effects on the spatial organization of cancer genomes.

Classes of ITD Predict Outcomes in AML Patients Treated with FLT3 Inhibitors.

PURPOSE: Recurrent internal tandem duplication (ITD) mutations are observed in various cancers including acute myeloid leukemia (AML), where ITD mutations in tyrosine kinase receptor FLT3 are associated with poor prognostic outcomes. Several FLT3 inhibitors (FLT3i) are in clinical trials for high-risk FLT3-ITD-positive AML. However, the variability of survival following FLT3i treatment suggests that the mere presence of FLT3-ITD mutations might not guarantee effective clinical response. Motivated by the heterogeneity of FLT3-ITD mutations, we investigated the effects of FLT3-ITD structural features on the response of AML patients to treatment.Experimental Design: We developed the HeatITup (HEAT diffusion for Internal Tandem dUPlication) algorithm to identify and quantitate ITD structural features including nucleotide composition. Using HeatITup, we studied the impact of ITD structural features on the clinical response to FLT3i and induction chemotherapy in FLT3-ITD-positive AML patients. RESULTS: HeatITup accurately identifies and classifies ITDs into newly defined categories of "typical" or "atypical" based on their nucleotide composition. A typical ITD's insert sequence completely matches the wild-type FLT3, whereas an atypical ITD's insert contains nucleotides exogenous to the wild-type FLT3. Our analysis shows marked divergence between typical and atypical ITD mutation features. Furthermore, our data suggest that AML patients carrying typical FLT3-ITDs benefited significantly more from both FLT3i and induction chemotherapy treatments than patients with atypical FLT3-ITDs. CONCLUSIONS: These results underscore the importance of structural discernment of complex somatic mutations such as ITDs in progressing toward personalized treatment of AML patients, and enable researchers and clinicians to unravel ITD complexity using the provided software.See related commentary by Gallipoli and Huntly, p. 460.

Differential Integration of Transcriptome and Proteome Identifies Pan-Cancer Prognostic Biomarkers.

High-throughput analysis of the transcriptome and proteome individually are used to interrogate complex oncogenic processes in cancer. However, an outstanding challenge is how to combine these complementary, yet partially disparate data sources to accurately identify tumor-specific gene products and clinical biomarkers. Here, we introduce inteGREAT for robust and scalable differential integration of high-throughput measurements. With inteGREAT, each data source is represented as a co-expression network, which is analyzed to characterize the local and global structure of each node across networks. inteGREAT scores the degree by which the topology of each gene in both transcriptome and proteome networks are conserved within a tumor type, yet different from other normal or malignant cells. We demonstrated the high performance of inteGREAT based on several analyses: deconvolving synthetic networks, rediscovering known diagnostic biomarkers, establishing relationships between tumor lineages, and elucidating putative prognostic biomarkers which we experimentally validated. Furthermore, we introduce the application of a clumpiness measure to quantitatively describe tumor lineage similarity. Together, inteGREAT not only infers functional and clinical insights from the integration of transcriptomic and proteomic data sources in cancer, but also can be readily applied to other heterogeneous high-throughput data sources. inteGREAT is open source and available to download from https://github.com/faryabib/inteGREAT.

A B Cell Regulome Links Notch to Downstream Oncogenic Pathways in Small B Cell Lymphomas.

Gain-of-function Notch mutations are recurrent in mature small B cell lymphomas such as mantle cell lymphoma (MCL) and chronic lymphocytic leukemia (CLL), but the Notch target genes that contribute to B cell oncogenesis are largely unknown. We performed integrative analysis of Notch-regulated transcripts, genomic binding of Notch transcription complexes, and genome conformation data to identify direct Notch target genes in MCL cell lines. This B cell Notch regulome is largely controlled through Notch-bound distal enhancers and includes genes involved in B cell receptor and cytokine signaling and the oncogene MYC, which sustains proliferation of Notch-dependent MCL cell lines via a Notch-regulated lineage-restricted enhancer complex. Expression of direct Notch target genes is associated with Notch activity in an MCL xenograft model and in CLL lymph node biopsies. Our findings provide key insights into the role of Notch in MCL and other B cell malignancies and have important implications for therapeutic targeting of Notch-dependent oncogenic pathways.

Functional proteogenomics reveals biomarkers and therapeutic targets in lymphomas.

Identification of biomarkers and therapeutic targets is a critical goal of precision medicine. N-glycoproteins are a particularly attractive class of proteins that constitute potential cancer biomarkers and therapeutic targets for small molecules, antibodies, and cellular therapies. Using mass spectrometry (MS), we generated a compendium of 1,091 N-glycoproteins (from 40 human primary lymphomas and cell lines). Hierarchical clustering revealed distinct subtype signatures that included several subtype-specific biomarkers. Orthogonal immunological studies in 671 primary lymphoma tissue biopsies and 32 lymphoma-derived cell lines corroborated MS data. In anaplastic lymphoma kinase-positive (ALK+) anaplastic large cell lymphoma (ALCL), integration of N-glycoproteomics and transcriptome sequencing revealed an ALK-regulated cytokine/receptor signaling network, including vulnerabilities corroborated by a genome-wide clustered regularly interspaced short palindromic screen. Functional targeting of IL-31 receptor ß, an ALCL-enriched and ALK-regulated N-glycoprotein in this network, abrogated ALK+ALCL growth in vitro and in vivo. Our results highlight the utility of functional proteogenomic approaches for discovery of cancer biomarkers and therapeutic targets.